Optimization with learning-informed differential equation constraints and its applications

dc.bibliographicCitation.firstPage3eng
dc.bibliographicCitation.journalTitleControl, optimisation and calculus of variations : COCVeng
dc.bibliographicCitation.volume28eng
dc.contributor.authorDong, Guozhi
dc.contributor.authorHintermüller, Michael
dc.contributor.authorPapafitsoros, Kostas
dc.date.accessioned2022-06-16T11:35:00Z
dc.date.available2022-06-16T11:35:00Z
dc.date.issued2022
dc.description.abstractInspired by applications in optimal control of semilinear elliptic partial differential equations and physics-integrated imaging, differential equation constrained optimization problems with constituents that are only accessible through data-driven techniques are studied. A particular focus is on the analysis and on numerical methods for problems with machine-learned components. For a rather general context, an error analysis is provided, and particular properties resulting from artificial neural network based approximations are addressed. Moreover, for each of the two inspiring applications analytical details are presented and numerical results are provided.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/9055
dc.identifier.urihttps://doi.org/10.34657/8093
dc.language.isoengeng
dc.publisherLes Ulis : EDP Scienceseng
dc.relation.doihttps://doi.org/10.1051/cocv/2021100
dc.relation.essn1262-3377
dc.rights.licenseCC BY 4.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/eng
dc.subject.ddc510eng
dc.subject.otherArtificial neural networkeng
dc.subject.otherIntegrated physics-based imagingeng
dc.subject.otherLearning-informed modeleng
dc.subject.otherOptimal controleng
dc.subject.otherQuantitative MRIeng
dc.subject.otherSemi-smooth Newton SQP algorithmeng
dc.subject.otherSemilinear PDEseng
dc.titleOptimization with learning-informed differential equation constraints and its applicationseng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorWIASeng
wgl.subjectMathematikeng
wgl.typeZeitschriftenartikeleng
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